Colorimetric matching the perception of a digital data file to hardcopy legacy

ABSTRACT

A system/method of color match assessment for electronic documents includes receiving digital data defining a composite electronic document including a raster image object having an edge and a color graphics object bordering the edge of the raster image object. The pixel color values defining the edge of the raster image object are processed to estimate a local color variance of the pixel color values. The local color variance is used to determine if the edge can be color matched to the bordering color graphics object. If the edge can be color matched, a match color for the edge is derived. The match color is associated with the digital data defining the electronic document so that a downstream object color match system can use the match color as needed.

BACKGROUND

It is not uncommon that a person possesses a legacy hardcopy that isdeemed satisfactory or even ideal, and also possesses the originalelectronic file comprising the digital image data on which the legacyhardcopy is based, and now desires to print one or more hardcopies thatmatch the legacy hardcopy. A problem arises when the legacy hardcopy isnot merely a print-out of the raw digital image data of the electronicfile but is, instead, a print of an enhanced or altered version of thedigital image data of the electronic file. For example, the legacyhardcopy can be a printed version of the original digital image datathat was enhanced by a technician to make the ocean more blue, to make asunset more orange, to make a headline font more red, etc.

One approach to the problem is to scan the legacy hardcopy to derivescanner image data from which the new hardcopies can be printed,essentially copying the hardcopy data. One drawback of this method isthat the legacy hardcopy might include artifacts such as fold-lines,coffee stains or other physical marks that must be excluded from anynewly generated hardcopy. Another drawback associated with the use of ascanner is that the original image data of the electronic file is, bydefinition, a perfect match to the legacy hardcopy, except for theabove-noted image enhancement, while data derived from scanning thelegacy hardcopy will include noise that will degrade the quality of anysubsequent prints.

Accordingly, a need has been identified for a system that allows newhardcopies to be printed from the original image data, wherein the newhardcopies are perceived to match the legacy hardcopy.

INCORPORATION BY REFERENCE

The following references are incorporated by reference in theirentirety:

-   U.S. Patent Application Publication No. 2004/0264781 to Eschbach et    al. and-   U.S. Patent Application Publication No. 2005/0134934 to Unal et al.

BRIEF DESCRIPTION

In accordance with one aspect of the present development, a method forcolor matching original image data to a printed hardcopy documentpreviously generated from the original image data comprises: inputtingthe original image data; scanning the printed hardcopy to derive andinput scanner image data that represent the printed hardcopy;identifying constant color objects in the original image data; for theconstant color objects in the original image data, identifyingrespective corresponding hardcopy color areas in the scanner image data;analyzing color differences between the constant color objects and thecorresponding hardcopy color areas to determine a printing deviceassumption to predict a printing device on which the printed hardcopydocument was previously printed; based upon the predicted printingdevice, converting at least the constant color objects and therespectively corresponding hardcopy color areas into a colorimetriccolor space; adjusting a color of at least one of the constant colorobjects to match a corresponding color of the respectively correspondinghardcopy color area in the colorimetric color space; determining atleast one measurement area located on the printed hardcopy document;measuring colorimetrically the at least one measurement area; comparingthe at least one measurement area to an expected color value; and,adjusting another color of at least another one of the constant colorobjects to match a corresponding color of the respectively correspondinghardcopy color area in the at least one measurement area.

In accordance with another aspect of the present development, a methodfor printing a new hardcopy using a legacy hardcopy and an electronicfile of the original image data is provided, wherein the legacy hardcopywas printed from a modified version of the original image data. Themethod comprises: inputting the original image data into an imageprocessing unit; scanning the legacy hardcopy to derive scanner datathat describe the legacy hardcopy and inputting the scanner data intothe image processing unit; identifying a plurality of different colorobjects in the original image data; identifying a plurality of differentcolor areas in the scanner data, wherein the plurality of color areascorrespond respectively to and result from the plurality of colorobjects identified in the original image data, wherein the color objectsand the color areas corresponding respectively thereto define aplurality of color pairs; converting the color pairs into a colorimetriccolor space; based on at least one color pair, creating a new mappingbetween digital input colors and requested print colors; additionally,determining at least one measurement area from the digital data that hasthe attribute of being visually relevant—i.e.: being of constant colorand large enough to form an accurate visual match—and creating acolorimetric measurement of the at least one measurement area; comparingthe at least one measurement area to an expected color value; and,adjusting another color of at least another one of the constant colorobjects to match a corresponding color of the respectively correspondinghardcopy color area in the at least one measurement area where dependenton the object type, the colorimetric adjustment is done locally in colorspace (i.e.: to that color alone) or the colorimetric measurement isused to refine color space.

In accordance with another aspect of the present development, a printingmethod comprises: inputting an electronic file comprising originaldigital image data; scanning a printed legacy hardcopy image that waspreviously printed from the electronic file to derive scanner imagedata; identifying a color area in the original digital image data;identifying a corresponding color area in the scanner image data thatcorresponds to the color area; defining an adjusted electronic filecomprising adjusted digital image data that represent the legacyhardcopy by adjusting a color of the color area in the original digitalimage data to match a corresponding color of the corresponding colorarea; determining from the electronic data file areas that are visuallyrelevant with respect to human color vision and creating a colorimetricmeasurement of the areas; and, using the colorimetric measurements toupdate the scanner based measurements in the previous step.

BRIEF DESCRIPTION OF THE DRAWINGS

The development comprises various steps and/or components and/orarrangements of same, embodiments of which are illustrated in theaccompanying drawings that form a part hereof, wherein:

FIG. 1 is a diagrammatic illustration of a first portion of a system andmethod in accordance with the present development;

FIG. 2 is a diagrammatic illustration of a second portion of a systemand method in accordance with the present development;

FIG. 3 illustrates a digital imaging apparatus for implementing a systemand method in accordance with the present development;

FIG. 4 displays an approximate object size for the standard 2° observerarea (i.e. at normal reading distance); and,

FIG. 5 displays an initial user Interface to create exemplary lab valuesfor an automatically determined number of locations on a legacyhardcopy.

DETAILED DESCRIPTION

The present development provides a system and/or method for generatingone or more new hardcopy prints from an electronic file comprisingoriginal digital image data, wherein the new hardcopy print(s) match alegacy hardcopy previously generated from the original digital imagedata of the electronic file, even when the legacy hardcopy was printedfrom an “enhanced” or “tuned” version of the original image data, i.e.,from a version of the original image data wherein color was adjustedsmoothly to provide the legacy hardcopy with certain desired visualcharacteristics or where the legacy hardcopy had been printed withoutproper color management as specified in the original electronic datafile.

The present development provides that four separate assumptions besatisfied: (i) a correspondence assumption, i.e., the electronic file isthe fundamental source for the legacy hardcopy; (ii) a satisfactionassumption, i.e., the person requesting one or more new hardcopies tomatch the legacy hardcopy is satisfied with certain aspects of thelegacy hardcopy, even if he/she cannot articulate these satisfactoryaspects; (iii) a marking technology assumption, i.e., the legacyhardcopy was printed using a known conventional or commercial marking(printing) technology known in the art (e.g., offset, xerography,inkjet, etc.) rather than by hand or using some unconventional printingtechnique; (iv) a small perturbation assumption, i.e., anyenhancement/modification of the original image data of the electronicfile to produce the legacy hardcopy was a limited and rational andsmooth change of the original image data rather than a radical orarbitrary operation. These four assumptions have a very high probabilityof being true in real-world imaging applications. If any of the aboveassumptions is not satisfied, the process generally will lead tounsatisfactory results.

FIG. 1 discloses a first aspect of the present development. Theelectronic file 10 comprising the original digital image data, which canbe supplied on a diskette, compact disk, portable memory device, or by anetwork connection or by other means, is input to a raster imageprocessor (RIP) 15, wherein the original image data are RIPped into“raw” raster image data, if not already in raster form, so that all pagedescription language (PDL) elements are converted to pixel data usingassociated cyan, magenta, yellow, black (cmyk) values. If the originalimage data are already in a raster form, e.g., cmyk TIFF data, the RIPprocess is skipped.

In a step 20, the raster data are segmented into pixel-based objects asis generally known in the digital imaging art, wherein each segmentedobject is defined by a discrete region of pixels defining a particulartype of object, e.g., text, a continuous tone photograph, a rasterimage, a graphics object, a halftone image, a background object, etc. Itshould be noted that this segmentation step is greatly simplified by theexistence of the electronic original. The electronic original objectsizes and locations can directly be used to identify the correspondingpage areas in the hardcopy scan. Using the correspondence assumptionabove, one knows that simple spatial transforms (scale, rotation, smallshears, and the like) can create spatial correspondence between scan andelectronic data and that the labeling of the scan data can subsequentlyderived from the electronic data. Note that the object type definitionsare functional and consistency is more important than agreement tohumanly applied labels.

In an attribute identification operation 25, at least some of thesegmented objects output by the segmentation operation 20 are processedto identify attributes that describe the object. The identifiedattributes may vary depending upon the type of object. For example, araster image is processed to identify attributes such as size, location,average color, color variance; a graphics object is processed toidentify attributes such as size, location, cmyk color value(s).Accurate knowledge of each individual pixel property is not arequirement for subsequent processing as described below, and thisprovides an advantage to the present development in terms of reducedprocessing complexity.

Based upon the above processing, in a color identification operation 30,objects of constant color are identified in the original imagedata—referred to herein as “constant color objects.” The term “constantcolor” is intended to encompass objects and areas defined by pixels ofidentical color values (e.g., a single-color graphics object) and/orobjects and areas defined by pixels with low color variance. This can beunderstood regarding the following example: a photo of a solid greenpaint area might have a mean of 166 in the green channel, at the sametime, the standard deviation of the patch might be 4 units. Or the photoof a red brick which would visually be considered “constant”, in theactual image data might have a mean of 185 in the red channel, at thesame time, the standard deviation of the patch might be 15 units.Preferably, as part of this color identification operation 30, onlyobjects of constant color above a pre-defined spatial size threshold areidentified, e.g., at least 1 cm by 1 cm in size or the equivalent of thetotal spatial area defined by the original image data. It is understoodthat the underlying assumption is that of visual relevance, meaning thatthe object/area is constant enough to be color compared by a human andthat the object/area is large enough to be color compared by a human.Based on the standard observer, i.e. a 2° field of view being the basisof colorimetric definitions, thus all areas that are considered asconstant should be at least of that size, which translates into roughlyone centimeter at a viewing distance of 30 cm. Larger areas will betreated preferentially with the 2° field being a reasonable lower boundfor the size. The constant color objects are identified in the step 30in order to guide subsequent processing due to the fact that: (i) theconstant color objects offer a higher visual distinction to a viewer ofa hardcopy image and are thus more likely to be a source of a perceivedmismatch between a new hardcopy and the legacy hardcopy; and, (ii) theconstant color objects in the original image data allow for theidentification of corresponding areas (i.e., areas printed based uponthe constant color object data) in the legacy hardcopy (and scannerimage data derived from the legacy hardcopy as described below).Examples of such constant color objects are large text areas (headlines)or logos or graphic elements, such as banners. Examples of constantcolor objects that show some variation in the digital data arecompressed color objects, scans of color objects embedded in the digitaldata and the like. Small elements including small text are ignored,because it is well known that small text cannot be judged accuratelywith respect to color.

With continuing reference to FIG. 1, it can be seen that the legacyhardcopy 100 is also processed according to the present development. Ina first operation 110, the legacy hardcopy is scanned to derive scannerimage data that represent the legacy hardcopy 100. The presentdevelopment provides that, for all or at least some of the originalconstant color objects identified in the original image data in step 30,a respective corresponding hardcopy color area be identified in thescanner image data. As such, in a step 120, the scanner image data fileis processed to identify hardcopy color areas in the scanner image datathat correspond respectively to, i.e., that were respectively printedbased upon, the constant color objects identified in the original imagedata. A constant color object and its corresponding hardcopy color arearepresented in the scanner image data are referred to herein as a “colorpair.” A 100% success rate for the step 120 is not required, i.e., it issufficient that at least one and preferably a plurality of color pairsbe identified. It is important to understand that two different“constant color” are used, namely a “constant color” as seen by ascanner for processing and a “constant color” that is humanly relevant.The “constant color” for the processing of scanner data in general ismuch smaller than the above mentioned 1 cm by 1 cm and is used toascertain that the color data is not an actual image edge. The humanrelevant “constant color” is much larger, as it is bound by thelimitations of the human visual system in terms of color matching fordifferent area sizes. In essence, measurement devices are able tomeasure areas smaller than those that are visually relevant.Hereinafter, the scanner relevant size will be assumed when constantcolor is discussed, unless noted otherwise.

At this stage, the original image data and scanner image data, at leastfor the color pairs, are converted to a colorimetric color space insteps 40,140, respectively. As used herein, “colorimetric color space”is intended to mean any color space that can be converted to a standardCIE color space. Examples of a colorimetric color space include CIELab,Xerox RGB, PhotoYCC, sRGB and the like. As is known in the art, however,the conversion of scanner image data from a device-dependent color spaceto a colorimetric space utilizes a printing/marking device assumption,i.e., an assumption about the marking device that printed the imagedata. The printing device for the legacy hardcopy 100 is unknown but thepossibilities are limited due to the “marking technology assumption”described above, i.e., that the legacy hardcopy was printed using aknown conventional marking (printing) technology known in the art (e.g.,offset, xerography, inkjet, etc.) rather than by hand or using someunconventional printing technique. In steps 40,140, at least one andpreferably more of the color pairs of the original image data andscanner image data are converted to a colorimetric color space using aplurality of different printing device assumptions.

In a step 50, a color difference is determined between the members ofeach color pair in the colorimetric color space, for each printingdevice assumption. In other words, for one or more color pairs, a firstcolor difference between the color pairs is determined for colorimetriccolor space data derived using a first printing device assumption; asecond color difference between the same color pairs is determined forcolorimetric color space data derived using a second printing deviceassumption; etc. Because the same printing device assumption is used forthe members of a color pair, the number of color space conversions andcolor difference calculations is reduced from N² to N. Additionaltechniques such as described in U.S. Patent Application Publication No.2004/0264781 to Eschbach et al. and U.S. Patent Application PublicationNo. 2005/0134934 to Unal et al., both of which documents are herebyexpressly incorporated by reference into the present specification, canbe used to further reduce the number of possible conversions.

In a step 60, the printing device assumption that provides the smallestcolor difference between the members of at least one and preferably allof the color pairs is selected as the printing device assumption to beused for the remainder of the matching process in accordance with thepresent development. It should be noted that the device assumptionselected in step 60 need not be “correct” in the sense that the legacyhardcopy 100 need not have been actually printed using the markingdevice corresponding to the selected device assumption.

As shown in FIG. 2, in a step 70, the entire original image data file(or at least the constant color object data) and the entire scanner datafile (or at least the hardcopy color area data) are converted to acolorimetric color space using the printing device assumption selectedin step 60. Note that the colorimetric color space for step 70 istypically the same as the colorimetric color space described above withreference to FIG. 1, but can be a different colorimetric color space.

As shown in FIG. 2, the original image data and scanner image data arethen both represented in a colorimetric color space, wherein the colorpairs differ from each other in terms of color by only a small amount,where small refers to an amount that is in the order of variationscommonly associated with machine variability and printenhancement/tuning. Then, a step 80 is carried out to smoothlyinterpolate the original image data so that the color difference foreach color pair is minimized. The step 80 can be completed in severalalternative variations. In one case, only those data corresponding tothe constant color objects are adjusted in the colorimetric color spaceto match the color of their respective corresponding hardcopy colorareas in the scanner data. In another embodiment, the entire originalimage data file is adjusted in the colorimetric color space so that eachconstant color object is adjusted to match the color of their respectivecorresponding hardcopy color areas in the scanner data. In either case,the color adjustment is carried out to adjust the average color of theobject (or complete file) as a whole rather than as an independentadjustment of individual pixel color values on a pixel-by-pixel basis,i.e., if a particular pixel value x is mapped to x+3, this mapping willbe done for all instances of the pixel value x instead of just certaininstances of the pixel value x. Also, the black and white “luminance”values are preferably not adjusted.

As noted above, the present development is dependent on a “smallperturbation assumption,” i.e., an assumption that any enhancement ofthe original image data of the electronic file 10 was a limited andrational and smooth tuning of the original image data rather than aradical or arbitrary operation to obtain the legacy hardcopy. Examplesof such a radical operation would be (1) the inversion of one channel,or (2) the exchange of the red and blue channel. As such, those ofordinary skill in the art will recognize that, if the small perturbationassumption is correct, smooth adjustment of the data defining theconstant color objects (with or without the remainder of the originalinput data) will be possible in a manner that will reduce the colordifference between each color pair.

A step 85 determines if color match between the color pairs is improved.This is accomplished by an automated calculation of the difference incolorimetric values and comparison of the difference to an acceptabletolerance threshold or, alternatively, by a user comparison of a videoscreen or proof print. If the color match is not improved, it is likelythat the small perturbation assumption is not valid for the legacyhardcopy 100, and a new hardcopy is printed in a step 90 a using theunmodified original image data file 10 as input to the printing process90 a or the process is terminated without any printing operation asindicated by the broken line. If the step 85 determines that color matchis improved because the color difference between one or more color pairsis reduced or eliminated, a step 90 b is carried out to print one ormore new hardcopies using the adjusted original image data as outputfrom the color-adjustment step 80 as input to the printing process 90 b.

FIG. 3 diagrammatically illustrates an example of a digital imageprocessing apparatus 200 in which the system/method of the presentdevelopment is implemented. The device comprises an input device 210 forinput of the original image data file 10 from a disk, CD, random accessmemory, computer workstation, network connection or other data source.The device also comprises a scanner 220 for scanning the legacy hardcopy100. The input device 210 and scanner 220 are connected to provide inputto an image processing unit IPU that comprises a combination of hardwareand software that perform digital image processing operations inaccordance with the present development. The image processing unit IPUis connected to an image output device PRT comprising a print engine fordepositing ink or toner on paper or another recording media in responseto the output of the image processing unit. Typically, the image outputdevice is a CMYK printer device as is known in the art.

It should be understood that the mapping between the color pairs can beimplemented in a variety of ways. The first and most common waydetermines a multi-dimensional look-up table relating digital countvalues from the electronic original to new digital count values thatshould be printed to reproduce the hardcopy output, minus its physicaldeficiencies as noise, inks and the like. In an alternateimplementation, the color pairs can be used to derive, e.g., viastandard regression, a transformation matrix of predetermineddimensionality. A simple form would be the derivation of a 3×3transformation matrix from the color pair data, or the derivation ofgain and offset parameters.

It should also be noted that in the table implementation, table valuesthat were not derived from the color pairs can be smoothly interpolatedfrom neighboring color pairs. And, in cases where noise suppression isdesired, a relaxation parameter can be used in such interpolationsbiasing the process towards the “no-operation” direction as is commonlydone in all image processing scenarios in the presence of noise.

A second step can be introduced to the process described above (i.e.first step) wherein the first step is subsequently augmented by acolorimetric second step (here, colorimetric refers to multi-channelmeasurement as done with a Gretag, XRite or similar devices) based onvisually relevant constant color areas.

A colorimetric match based on scanner data is only an approximation to acolorimetric match created by an actual colorimetric measurement device.However, the advantage of the scanner match is the easy access to manymeasurement points—essentially every pixel in the image that is deemedto be in a color constant region—and the resulting fast match for alarge amount of points. Considering the widespread use of scanners forimage reproduction, one also can understand that the approximate matchis sufficient in a large number of applications.

In order to improve on the so-far described scanner-based match, one cansubsequently augment the large number of color match pairs with a smallnumber of color match pairs that are generated by a colorimetricmeasurement device in areas of the image that are visually relevant.

It is to be appreciated from simple size considerations that there willalways be fewer visually relevant constant color areas than there willbe areas that are considered constant color areas for the purpose ofcolor matching through the scanning process. It is thus an intention toidentify a small set of visually relevant constant color areas and touse the information gathered from these areas in a second step toupdate/modify the color matching obtained from the scanner-based colorpairs in the first step.

It is understood that this problem cannot be solved by standardcolorimetric approaches. First, it is not evident that any type ofmeasurement patches or control fields are available on the legacy print(i.e. hardcopy print 100). Secondly, even if control patches wereavailable, these would normally cover only very few colors of the entiregamut. Thus, it is desirable to have a system that derives thecalibration colors from arbitrary document content.

As part of scanner-based color matching, some underlying processing canbe performed that was not mentioned above. For one, the geometricalmatching of the paper copy and the electronic copy can be performedleading to a well defined geometrical relationship between the legacypaper document and the digital source. For example, the paper documentmight have been printed with an image shift on the device, e.g.increasing the top margin and reducing the bottom margin, and/or thelegacy document. Further, manual additions might have been added to thelegacy document, like handwritten markings, punch-holes and staples andthese areas are also known since they resulted in a clear color mismatchbetween the scanner and electronic data. Even further, unintentionalchanges like smears, fold lines, etc can also result in image areas thatcannot be matched and thus are known. It is important, that for thepurpose of the matching, one only needs to know that two areas could notreliably be matched, i.e.: their color difference was too large to beconsidered, and that it is not necessary to know or identify the causefor this mismatch. The above mentioned examples are only to illustratethat the system internally would only distinguish areas that can bematched and areas that cannot be matched.

After the first step, one has a color transformation that is accurate towithin some common scanner/copier quality parameter. This may not beenough for some cases, for example, if large constant colors make avisual comparison easy. However, the notion of colorimetric match for“small” areas does not firmly exist. Illustratively, a small area canassume a 2° observer area which is a patch having a diameter of 1 cm or0.5 inch as is shown in FIG. 4.

It is important that any visual color differences between electronic andpaper copy apply to some large object on the print. Aspects of thisdisclosure are thus to identify those areas, to create a colorimetricmeasurement of those areas, and to use the colorimetric data toupdate/modify the original color transform created based on the scannerdata. As part of the geometric matching of digital and paper copy, onecan identify object types and certain object attributes (wrt color)inside the system. One of the identified properties can be described as“constant color” as well as the precise location of that area on bothpaper and electronic document. These areas are small from a humanobserver perspective, but large enough to eliminate halftoning effectsand large enough to detect edge transitions in the scan.

One can now examine these “constant color” areas and sort them by size.This can be done exemplary by flood-filling the individual areas andcreating a total pixel count (area) as well as an indication ofcompactness (e.g.: aspect ratio). From that, a sorting table of N′entries can be determined that lists the individual areas by their size(i.e. descending order). It is to be appreciated that the “size” is adeterminant of visual importance. The table can then be pruned to havethe N most relevant colors of the document, along with their currentcolor value, their digital color value (from the source digital file)and the corresponding physical locations and geometry. This informationcan now be used to create colorimetric values from the user in asemi/automatic way. It is to be appreciated that there will always bemore constant color areas for the purpose of scanner matching than thereare visually relevant constant color areas, thus the N relevant colorswill always be a much smaller set than the N′ elements of the overalltable. In general, one can assume that there are only a handful of areason a page that have visually relevant constant colors, i.e. commonlythree or four, but typically not more than approximately ten for astandard page size.

In a semi-automatic adjustment, a communication with the user can beestablished to determine what area of the page has to be measuredoff-line. This can be done by showing a sample of the document, withmarkings like “circles” or “rectangles” overlayed that indicate themeasurement area. FIG. 5 shows a screenshot of such a display. It is tobe appreciated that the areas (Area 0-Area 5) to be measured containrelatively large constant color areas. In this manner, the user canposition the colorimeter inside the correct general area and thus nofine manual adjustments are needed.

As can be seen from FIG. 5, individual image areas 300, 310, 320, 330,340, 350 are numbered and displayed to the user. These areas are createdautomatically and the total number of areas is a function of the actualdocument content. In most documents, only two or three document areasare determined, since most pages do not contain a multitude of largeconstant color areas.

In one arrangement, the number of measurement areas, i.e. rectangles,created can follow a “preset” which identifies minimum area size, aswell as maximum area number. The rectangles can be, for example, 1 inchsquare or larger, in order to be easily measurable by a human.

Alternatively to the display version, the user can print a sheet thatshows the document along with the indicated areas. This is useful if themeasurement device is in a separate room from the scanner/monitor.

In one fully automatic method, the geometrical data displayed to theuser in the semi-automatic way is directly transmitted to a roboticcolorimetric measurement device, where any device that is capable ofbeing positioned to an arbitrary spot by automatic means is consideredsufficient.

As described, the colorimetric measurement has now generated a few labvalues that can be used by the system to update the color transform.Since this is a subsequent step, one can expect all entered lab valuesto be in relatively close proximity—in terms of lab—to the scannercreated values. In the color adjustment, one can distinguish betweendifferent object types and the updating mechanism can be useddifferently for the different types. It is to be appreciated that thelocation and type of all objects on the scanned page are known. Twotypes are briefly outlined hereinafter. One type of object is a constantfill. Constant fills are a trivial extreme in print scenarios. In thiscase, only that specific color needs to be modified. Since all objecttypes have their own transforms attached, this only influences aspecific color of a specific object type. Another type of object is animage file. Image files rarely have a large constant area, however, thisis still occurring inside the PDF. In this scenario, the newlycolorimetrically measured color has to update a complete ICC profile.This can be done in two basic ways as described hereinafter. Theoriginal color value (scanner generated) can be replaced by thecolorimetrically obtained value. This can also include attaching thestatistical relevance (frequency of occurrence) from the original colorvalue to the new colorimetric value, i.e. the area size weighting ismaintained. This essentially is re-running the original color value ICCcreation with a partially different set of data. Alternatively, thecolorimetric value can be used to modify the original color value outputtable. In this case, the colorimetric value is used as a “shift” toglobally move the transform computed by the original color value. Thisshift can be done while maintaining some anchors (black, white). In thisscenario, it can be assumed that the scanner response used in originalcolor value is the equivalent of a “cast” influencing large parts ofcolor space and not the individual color.

It is to be understood that the restriction to “constant” areas is madefor convenience. There are objects that are not constant but still havea good chance of being accurately measured. An example is a sweepbetween to different colors. Since the “edge” of the sweep is veryunderstandable in “human terms”, one can expect an accurate measurementfor those areas, especially, since there is an error checking in theinputting step, as mentioned above.

It is to be appreciated that from the scan and colorimetric update, noclear statement can be made for the underlying reason of the differencebetween colorimetric data and scanner data. In essence, one cannot knowif the scanner ΔE was systematic, i.e. caused by using an inappropriateprofile offset|photo|xerographic|inkjet, or if it was just the expectedΔE caused by the scanner calibration. Correspondingly, one cannotautomatically, at this point, select between the two approaches.

Optimizing the selection not based on best performance, but onfail-safety, one can chose to implement (as default) the first approach.Again, in this approach, one can substitute the scanner created labvalue by the colorimetrically generated lab value and start the originalcolor value process with this new input data.

Creating a “ProofMatch” upgrade of the existing original color valuetechnology can be done by starting with the basic approach. Rather thancompleting the calculation, the ProofMatch interface will create anintermediate stop-point at which colorimetric data can be enteredmanually or automatically.

One advantage of this approach is that all areas that would lendthemselves to a colorimetric verification by a user will have acolorimetric match. Only the page locations that are part of a complexscene or are too small for colorimetry will not be colorimetricallymatched. Thus all places that a user can “see”, i.e. the 2° observer,will be perfectly matched and in all other areas, the term “color match”has no visual relevance.

While particular embodiments have been described, alternatives,modifications, variations, improvements, and substantial equivalentsthat are or may be presently unforeseen may arise to applicants orothers skilled in the art. Accordingly, the claims as filed and as theymay be amended are intended to embrace all such alternatives,modifications variations, improvements, and substantial equivalents.

What is claimed is:
 1. A method for color matching original image datato a printed hardcopy document previously generated from said originalimage data, said method comprising: inputting said original image data;scanning said printed hardcopy to derive and input scanner image datathat represent said printed hardcopy; identifying constant color objectsin said original image data; for said constant color objects in saidoriginal image data, identifying respective corresponding hardcopy colorareas in said scanner image data; analyzing color differences betweensaid constant color objects and the corresponding hardcopy color areasto determine a printing device assumption to predict a printing deviceon which said printed hardcopy document was previously printed; basedupon said predicted printing device, converting at least said constantcolor objects and said respectively corresponding hardcopy color areasinto a colorimetric color space; adjusting a color of at least one ofthe constant color objects to match a corresponding color of therespectively corresponding hardcopy color area in said colorimetriccolor space; determining at least one measurement area located on saidprinted hardcopy document; measuring colorimetrically said at least onemeasurement area; comparing said at least one measurement area to anexpected color value; and, adjusting another color of at least anotherone of the constant color objects to match a corresponding color of therespectively corresponding hardcopy color area in said at least onemeasurement area.
 2. The method as set forth in claim 1, furthercomprising: determining at least another measurement area located onsaid printed hardcopy document.
 3. The method as set forth in claim 2,wherein the total number of measurement areas is a function of theactual document content.
 4. The method as set forth in claim 3, whereinthe measurement areas are rectangles.
 5. The method as set forth inclaim 4, wherein said rectangles are at least one inch square.
 6. Themethod as set forth in claim 1, wherein said at least one measurementarea is from about 0.7 cm to about 1.3 cm in diameter.
 7. The method asset forth in claim 1, wherein said at least one measurement areaincludes a large constant color area.
 8. The method as set forth inclaim 1, wherein said at least one measurement area is createdautomatically.
 9. A method for printing a new hardcopy using a legacyhardcopy and an electronic file comprising original image data, whereinthe legacy hardcopy was printed from a modified version of the originalimage data, said method comprising: inputting said original image datainto an image processing unit; scanning said legacy hardcopy to derivescanner data that describe said legacy hardcopy and inputting saidscanner data into said image processing unit; identifying a plurality ofdifferent color objects in said original image data; identifying aplurality of different color areas in said scanner data, wherein saidplurality of color areas correspond respectively to and result from saidplurality of color objects identified in said original image data, andwherein the color objects and the color areas corresponding respectivelythereto define a plurality of color pairs; converting the color pairsinto a colorimetric color space; based on at least one color pair,creating a mapping between digital input colors and requested printcolors; determining at least one measurement area from the digital datathat has the attribute of being visually relevant and creating acolorimetric measurement of said at least one measurement area;comparing said at least one measurement area to an expected color value;and, adjusting another color of at least another one of the constantcolor objects to match a corresponding color of the respectivelycorresponding hardcopy color area in said at least one measurement area,wherein dependent on the object type; the colorimetric adjustmentselectively is done locally in color space or the colorimetricmeasurement is used to refine color space.
 10. The method as set forthin claim 9, further comprising: determining at least another measurementarea located on said printed hardcopy document.
 11. The method as setforth in claim 10, wherein the total number of measurement areas is afunction of the actual document content.
 12. The method as set forth inclaim 11, wherein the measurement areas are rectangles.
 13. The methodas set forth in claim 12, wherein said rectangles are at least one inchsquare.
 14. The method as set forth in claim 9, wherein said at leastone measurement area is from about 0.7 cm to about 1.3 cm in diameter.15. The method as set forth in claim 9, wherein said at least onemeasurement area includes a large constant color area.
 16. The method asset forth in claim 9, wherein said at least one measurement area iscreated automatically.
 17. A printing method comprising: inputting anelectronic file comprising original digital image data; scanning aprinted legacy hardcopy image that was previously printed from saidelectronic file to derive scanner image data; identifying a color areain said original digital image data; identifying a corresponding colorarea in said scanner image data that corresponds to said color area;defining an adjusted electronic file comprising adjusted digital imagedata that represent said legacy hardcopy by adjusting a color of thecolor area in said original digital image data to match a correspondingcolor of the corresponding color area; determining from the electronicdata file areas that are visually relevant with respect to human colorvision; creating a colorimetric measurement of said areas; and, usingthe colorimetric measurements to update the scanner based measurementsin the previous step.
 18. The method as set forth in claim 17, furthercomprising: determining at least another measurement area located onsaid printed hardcopy document.
 19. The method as set forth in claim 17,wherein said at least one measurement area is from about 0.7 cm to about1.3 cm in diameter.
 20. The method as set forth in claim 17, whereinsaid at least one measurement area includes a large constant color area.21. The method as set forth in claim 17, wherein the total number ofmeasurement areas is a function of the actual document content.
 22. Themethod as set forth in claim 17, wherein the measurement areas arerectangles.